Domain Obfuscation for Efficient Secure Aggregation of Sparse Feature Vectors
Amit Tulsidas Chaulwar · 2025
To collaboratively compute the sum of user private feature vectors, secure aggregation protocols are used to preserve the users’ privacy. The existing protocols are expensive in terms of computational/communication costs, making them impractical where the feature vectors are of size in thousands or millions. Also, they do not provide a possibility to define their own privacy and computation budget. In this work, we propose the Domain Obfuscated Secure Aggregation (DO-SAFE) protocol that allows users to define their privacy budget as per their preference. Our theoretical analysis demonstrates that the proposed protocol can significantly reduce communication and computation costs.